MAPO: mining API usages from open source repositories

By Tao Xie, Jian Pei. 2006

247 citations recorded by the source corpus.

Subfields: Information Systems, Code Generation & Program Synthesis, Program Analysis & Verification

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Charles Sutton
2. Tien Nhut Nguyen
3. Jaroslav M. Fowkes
4. Miltiadis Allamanis
5. Premkumar T. Devanbu
6. Anh Tuan Nguyen
7. Tung Thanh Nguyen
8. Rishabh Singh

In Code Generation & Program Synthesis

1. Charles Sutton
2. Miltiadis Allamanis
3. Jaroslav M. Fowkes
4. Tien Nhut Nguyen
5. Hamid Reza Shahriari
6. Seyed Mohammad Ghaffarian
7. Andreas Zeller
8. Christian Lindig

In Program Analysis & Verification

1. Charles Sutton
2. Tien Nhut Nguyen
3. Jaroslav M. Fowkes
4. Hamid Reza Shahriari
5. Seyed Mohammad Ghaffarian
6. Hoan Anh Nguyen
7. Miltiadis Allamanis
8. Tung Thanh Nguyen

Citations in the corpus

• Graph-based mining of multiple object usage patterns (2009, methodology): “Similar tools include Prospector [22] and MAPO [32].”
• Mining API patterns as partial orders from source code: from usage scenarios to specifications (2007, methodology): “[26] T. Xie and J. Pei.”
• Semantic code search via equational reasoning (2020, background): “MAPO [91] is similar, but creates its database by merging static sequences of API calls.”
• What makes a good code example?: A study of programming Q&A in StackOverflow (2012, background): “Some of them use mining technique to locate features [17, 22]; others extract common API usage patterns [1, 2, 30].”
• Autofolding for Source Code Summarization (2014, methodology): “Work in this area includes synthesis of API usage examples [37], extraction of API usage patterns [38], [39], and generation of natural language summaries for source code [12], [13].”
• MAPO: Mining and Recommending API Usage Patterns (2009, background): “MAPO is extended from its previous version [38], and the main differences are as follows.”
• Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques (2017, methodology): “The approach consists of four main steps and is based on a previous work by a few of the authors named MAPO (Xie and Pei 2006).”
• Detecting object usage anomalies (2007, methodology): “Tools that address this problem include MAPO by Xie and Pei [35], P ROSPECTOR by Mandelin et al. [24] and XS NIPPET by Sahavechaphan and Claypool [29].”
• Parameter-free probabilistic API mining across GitHub (2015, methodology): “We use an approach similar to the original MAPO paper [41] to approximately resolve fully qualified method names.”
• Parameter-Free Probabilistic API Mining at GitHub Scale (2015, methodology): “The first algorithm for mining API usage patterns from source code was MAPO, proposed by Xie and Pei [37] and extended by Zhong et al. [39].”